Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Small_2023_Global with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Small_2023_Global with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Small_2023_Global") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Small_2023_Global", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f63abd5aa857757e392da63ca2701a46775846fb1f5186188c543069d87c377
- Size of remote file:
- 185 MB
- SHA256:
- fc772ec5799c0bd7c11322dc8731dfda60c17e66d6b12d780e0011a5a7550402
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